{"type": "root", "children": [{"type": "p", "children": [{"type": "t", "text": "\n CT47A7 is a member of the cancer/testis (CT) antigen family, a group of genes that under normal circumstances are expressed exclusively in germ cells but are aberrantly activated in various cancers. This selective expression profile makes CT47A7—and related CT antigens—attractive targets for both diagnostic biomarker development and immunotherapeutic strategies. In malignancies such as estrogen receptor–negative breast cancers, CT antigens have been associated with aggressive tumor characteristics and a pronounced immune response, suggesting that CT47A7 may similarly serve as a marker for identifying high‐risk lesions and potentially guiding targeted immune intervention."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "1"}]}, {"type": "t", "text": " \n Furthermore, autoantibody responses against CT antigens have been detected in patient serum, as observed in studies investigating prostate cancer, where differential expression levels of several CT antigens contributed to the identification of novel diagnostic and therapeutic biomarkers."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "2"}]}, {"type": "t", "text": " \n Comprehensive transcriptome analyses, such as those provided by the CHESS database, have expanded our catalog of human genes and transcripts, underscoring the importance of distinguishing functional CT antigens like CT47A7 from transcriptional noise."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "3"}]}, {"type": "t", "text": " \n Finally, integrative approaches that combine genomic profiling with advanced machine learning have further highlighted the potential role of such biomarkers in predicting cancer survivability and tailoring therapy, thereby emphasizing the clinical relevance of CT47A7 in personalized treatment strategies."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "4"}]}, {"type": "t", "text": "\n "}]}, {"type": "rg", "children": [{"type": "r", "ref": 1, "children": [{"type": "t", "text": "Otavia L Caballero, Sami Shousha, Qi Zhao, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Expression of Cancer/Testis genes in ductal carcinoma in situ and benign lesions of the breast."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Oncoscience (2013)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.18632/oncoscience.4"}], "href": "https://doi.org/10.18632/oncoscience.4"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "25593980"}], "href": "https://pubmed.ncbi.nlm.nih.gov/25593980"}]}, {"type": "r", "ref": 2, "children": [{"type": "t", "text": "Henry A Adeola, Muneerah Smith, Lisa Kaestner, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Novel potential serological prostate cancer biomarkers using CT100+ cancer antigen microarray platform in a multi-cultural South African cohort."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Oncotarget (2016)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.18632/oncotarget.7359"}], "href": "https://doi.org/10.18632/oncotarget.7359"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "26885621"}], "href": "https://pubmed.ncbi.nlm.nih.gov/26885621"}]}, {"type": "r", "ref": 3, "children": [{"type": "t", "text": "Mihaela Pertea, Alaina Shumate, Geo Pertea, et al. "}, {"type": "b", "children": [{"type": "t", "text": "CHESS: a new human gene catalog curated from thousands of large-scale RNA sequencing experiments reveals extensive transcriptional noise."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Genome Biol (2018)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1186/s13059-018-1590-2"}], "href": "https://doi.org/10.1186/s13059-018-1590-2"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "30486838"}], "href": "https://pubmed.ncbi.nlm.nih.gov/30486838"}]}, {"type": "r", "ref": 4, "children": [{"type": "t", "text": "Ashraf Abou Tabl, Abedalrhman Alkhateeb, Waguih ElMaraghy, et al. "}, {"type": "b", "children": [{"type": "t", "text": "A Machine Learning Approach for Identifying Gene Biomarkers Guiding the Treatment of Breast Cancer."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Front Genet (2019)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.3389/fgene.2019.00256"}], "href": "https://doi.org/10.3389/fgene.2019.00256"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "30972106"}], "href": "https://pubmed.ncbi.nlm.nih.gov/30972106"}]}]}]}